[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"retinal-vein-occlusion-rvo\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:retinal-vein-occlusion-rvo":28},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,5,0,[8,43,73,102,125],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":4,"overallStatus":30,"whyStopped":4,"lastUpdateSubmitDate":31,"lastUpdatePostDateStruct":32,"startDateStruct":35,"completionDateStruct":37,"leadSponsor":39,"locationsCount":42},"100618219","ai-vs-physician-for-anti-vegf-decision-making-an-rct-100618219",false,"NCT07328776","AI vs. Physician for Anti-VEGF Decision-Making: An RCT","An Artificial Intelligence System for Anti-VEGF Treatment Decisions in Retinal Diseases: A Randomized Controlled Trial","Inclusion Criteria:\n\nPatients with a diagnosis of nAMD, DME, and RVO; Patients who have completed the loading-dose treatment of anti-VEGF agents; Patients who were willing to participate and provided written informed consent.\n\nExclusion Criteria:\n\nRefusal to undergo OCT testing; Refusal to complete the 3-month follow-up period; Screening for a history of intraocular surgery within the past 6 months; Subjects with severe systemic diseases, intellectual developmental disorders, psychiatric illnesses, etc.","ALL","50 Years","85 Years",{"count":20,"type":21},200,"ESTIMATED","INTERVENTIONAL",[24],"NA","We developed an artificial intelligence system, called QiLin, which was designed to assist anti-VEGF treatment decisions in retinal diseases. QiLin was trained and validated via over 20,000 optical coherence tomography images from multicenter datasets, demonstrating strong performance on both internal and external validation. To evaluate its real-world clinical utility, we conducted a randomized controlled trial that rigorously compares the accuracy of treatment decisions between a physician-only arm and an AI-assisted physician arm.",[27,28,29],"DME","Retinal Vein Occlusion (RVO)","Neovascular (Wet) Age-Related Macular Degeneration","NOT_YET_RECRUITING","2026-05-18",{"date":33,"type":34},"2026-05-22","ACTUAL",{"date":36,"type":21},"2026-05-25",{"date":38,"type":21},"2026-10-15",{"name":40,"class":41},"Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine","OTHER",2,{"id":44,"slug":45,"hasResults":11,"nctId":46,"briefTitle":47,"officialTitle":48,"acronym":4,"eligibilityCriteria":49,"healthyVolunteers":50,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":51,"targetDuration":53,"studyType":54,"phases":4,"briefSummary":55,"conditions":56,"keywords":4,"overallStatus":30,"whyStopped":4,"lastUpdateSubmitDate":64,"lastUpdatePostDateStruct":65,"startDateStruct":67,"completionDateStruct":69,"leadSponsor":71,"locationsCount":4},"100615388","retinal-clinical-assessment-with-ai-derived-quantitative-information-100615388","NCT07291960","Retinal Clinical Assessment With AI-derived Quantitative Information","AI-derived Retinal Quantification Versus Routine Clinical Interpretation in Ophthalmic Assessment: a Randomized Controlled Trial","Inclusion Criteria:\n\nClinician Participants (Report Writers)\n\n1. Board-certified ophthalmologists or ophthalmology trainees (registrars or fellows) with clinical experience in interpreting fundus images.\n2. Capable of independently completing retinal clinical reports based on fundus photography.\n3. Willing and able to participate in the study tasks (report writing) under assigned study conditions.\n4. Able to provide informed consent.\n\nExpert Evaluators (Outcome Assessors)\n\n1. Senior ophthalmologists with at least 5 years of post-certification clinical experience.\n2. Not involved in the report-writing stage of the study.\n3. Willing to evaluate de-identified reports across predefined quality dimensions.\n4. Able to provide informed consent.\n\nFundus Images (Data Inputs)\n\n1. Retinal fundus photographs of sufficient quality for clinical interpretation.\n2. Images representing a range of common retinal findings (normal or abnormal).\n3. Previously collected, de-identified images with no patient-identifiable information.\n\nExclusion Criteria:\n\nClinician Participants\n\n1. Lack of experience in interpreting fundus images (e.g., interns, medical students).\n2. Prior involvement in the development, training, or validation of the AI system being tested.\n3. Inability to complete reporting tasks due to time constraints or technical limitations.\n4. Any condition that may interfere with ability to perform study tasks (e.g., prolonged absence).\n\nExpert Evaluators\n\n1. Participation in the intervention or control reporting arms.\n2. Prior exposure to or involvement in development of the AI system.\n3. Any conflict of interest affecting impartiality of report quality evaluation.\n\nFundus Images\n\n1. Poor-quality images with insufficient clarity for interpretation.\n2. Images containing artifacts or cropping that prevent accurate segmentation or assessment.\n3. Images with any remaining patient identifiers (excluded to maintain confidentiality).",true,{"count":52,"type":21},29,"21 Days","OBSERVATIONAL","This randomized controlled trial evaluates whether providing clinicians with AI-derived quantitative retinal information improves the quality and efficiency of retinal clinical assessment. Participating ophthalmologists and ophthalmology trainees will be randomly assigned to one of two groups. The intervention group will write clinical reports with access to automated quantitative measurements generated from fundus image analysis, including multiple retinal structural and vascular biomarkers. The control group will complete the same reporting tasks using only the original fundus images without AI-generated quantitative information.\n\nAll reports produced by both groups will be de-identified and independently evaluated by a separate panel of senior ophthalmologists who are blinded to group allocation. The expert evaluators will assess report accuracy, completeness, clarity, and overall clinical quality using predefined scoring criteria. The study aims to determine whether access to quantitative retinal biomarkers enhances clinicians' reporting performance and reduces reporting time during retinal assessment tasks.",[57,58,59,60,61,62,63,28],"no Obvious Abnormalities","Diabetic Retinopathy (DR)","AMD","Cup-to-disc Ratio Bigger Than 0.5","Pathological Myopia","Macular Hole","Epiretinal Membrane","2026-04-28",{"date":66,"type":34},"2026-04-29",{"date":68,"type":21},"2026-04-15",{"date":70,"type":21},"2026-05-15",{"name":72,"class":41},"Beijing Tongren Hospital",{"id":74,"slug":75,"hasResults":11,"nctId":76,"briefTitle":77,"officialTitle":78,"acronym":4,"eligibilityCriteria":79,"healthyVolunteers":11,"sex":16,"minAge":80,"maxAge":81,"enrollmentInfo":82,"targetDuration":4,"studyType":22,"phases":84,"briefSummary":86,"conditions":87,"keywords":88,"overallStatus":91,"whyStopped":4,"lastUpdateSubmitDate":92,"lastUpdatePostDateStruct":93,"startDateStruct":95,"completionDateStruct":97,"leadSponsor":99,"locationsCount":101},"100603201","phase-4-mecobalamin-combined-with-anti-vegf-intravitreal-injection-for-retinal-vein-occlusion-treatment-100603201","NCT07133438","Mecobalamin Combined With Anti-VEGF Intravitreal Injection for Retinal Vein Occlusion Treatment","Mecobalamin Combined With Anti-VEGF Intravitreal Injection for Treatment Retinal Vein Occlusion: a Double-blind Randomized Controlled Trial","Inclusion Criteria:\n\nDiagnosis of RVO meeting the international diagnostic criteria 4,12, age 18-80 years, gender not limited Treatment-naive RVO-ME (no prior anti-VEGF, glucocorticoid, or laser therapy) The CST is confirmed to be ≥300μm by OCT The baseline BCVA (ETDRS letter count) was 20\u002F400 to 20\u002F40 (34-78 letters) Signed informed consent and ability to comply with follow-up.\n\nExclusion Criteria:\n\nCombined with other eye diseases that cause ME (such as diabetic retinopathy, uveitis) Media opacities affecting imaging (such as severe cataract, vitreous hemorrhage) Prior anti-VEGF, steroid, or macular laser therapy Systemic use of glucocorticoids or immunosuppressants within 3 months Uncontrolled systemic disease (hypertension, diabetes, hepatic\u002Frenal dysfunction); pregnant or lactating women Allergy to mecobalamin or conbercept Unable to cooperate with examinations or follow-up, or participate in other clinical trials within one year","18 Years","80 Years",{"count":83,"type":21},120,[85],"PHASE4","Retinal vein occlusion (RVO), a common retinal vascular disease, is frequently treated with anti-vascular endothelial growth factor (anti-VEGF) agents as first-line therapy. However, anti-VEGF monotherapy lacks neuroprotective effects, primarily targets vascular leakage and neovascularization, and requires frequent long-term injections that impose substantial economic burdens. Combined therapeutic strategies addressing both vascular pathology and neural damage are therefore being explored.\n\nThis article describes the protocol for a randomized, outcome-blinded, placebo-controlled clinical trial evaluating mecobalamin (a widely used neuroprotective drug) in combination with anti-VEGF for the treatment of macular edema (ME). A total of 120 eligible RVO patients will be enrolled from the First Affiliated Hospital of Chongqing Medical University. Participants will be randomly assigned (1:1) to an experimental group and a control group. The experimental group will receive conventional anti-VEGF therapy plus oral mecobalamin capsules for 6 months, while the control group will receive the same anti-VEGF treatment plus a placebo for 6 months. All patients will undergo one year of follow-up after initial treatment, with visits at 1, 3, 6, 9, and 12 months.\n\nThe primary outcome is the change in central subfield thickness (CST) from baseline to one year post-initial treatment. Secondary outcomes include:\n\n* Change in best-corrected visual acuity (BCVA) from baseline over time,\n* Capillary density,\n* Cone photoreceptor distribution characteristics,\n* Mean light sensitivity and fixation stability,\n* Serum vitamin B12 levels,\n* Number of anti-VEGF treatments,\n* Injection frequency (times per year),\n* Treatment interval,\n* Incidence and severity of adverse events (AEs) and serious adverse events (SAEs).\n\nThis trial evaluates a novel \"neuroprotection + vascular intervention\" strategy combining mecobalamin with anti-VEGF therapy. The trial aims to provide high-level evidence for synergistic RVO treatment, with the potential to reduce recurrence rates and improve long-term visual function prognosis.",[28],[28,89,90],"Macular edema","Anti-VEGF","RECRUITING","2026-02-24",{"date":94,"type":34},"2026-02-27",{"date":96,"type":34},"2025-08-01",{"date":98,"type":21},"2027-07-31",{"name":100,"class":41},"First Affiliated Hospital of Chongqing Medical University",1,{"id":103,"slug":104,"hasResults":11,"nctId":105,"briefTitle":106,"officialTitle":107,"acronym":4,"eligibilityCriteria":108,"healthyVolunteers":11,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":109,"targetDuration":4,"studyType":54,"phases":4,"briefSummary":111,"conditions":112,"keywords":4,"overallStatus":30,"whyStopped":4,"lastUpdateSubmitDate":116,"lastUpdatePostDateStruct":117,"startDateStruct":119,"completionDateStruct":121,"leadSponsor":123,"locationsCount":4},"100612109","high-throughput-large-model-based-ai-assisted-diagnosis-using-oct-100612109","NCT07249307","High-throughput Large-model-based AI-assisted Diagnosis Using OCT","Study on Key Technologies for High-throughput Large-model-based AI-assisted Diagnosis Using OCT","Inclusion Criteria:\n\n* 1\\. Patients of any age or sex who undergo OCT and\u002For OCT angiography (OCTA) examinations as part of routine clinical care at Peking Union Medical College Hospital.\n\n  2\\. Clinical diagnosis of at least one of the following conditions: Diabetic retinopathy, Branch retinal vein occlusion, Central retinal vein occlusion, Age-related macular degeneration, Pathologic myopia with choroidal neovascularization and Glaucoma with optic nerve damage.\n\n  3\\. Imaging quality sufficient for analysis based on predefined OCT\u002FOCTA quality control criteria.\n\n  4\\. Ability to provide informed consent (for prospective participants), or availability of medical records that meet institutional ethical requirements (for retrospective data).\n\nExclusion Criteria:\n\n\\- 1. Poor-quality OCT\u002FOCTA images that do not meet analysis standards (e.g., severe motion artifacts, media opacity, incomplete scans).\n\n2\\. Patients unable to cooperate with standard ophthalmic imaging procedures. 3. Any condition judged by investigators to preclude accurate imaging evaluation or reliable diagnostic interpretation.",{"count":110,"type":21},2000,"This observational study aims to establish key technologies for high-throughput, large-model-based AI-assisted diagnosis using optical coherence tomography (OCT) and OCT angiography (OCTA). The study will collect real-world OCT\u002FOCTA images and corresponding clinical information from patients with common blinding retinal and optic nerve diseases at Peking Union Medical College Hospital.\n\nA high-throughput diagnostic framework based on large-scale artificial intelligence models will be developed and evaluated. The primary objective is to determine the diagnostic performance of the AI system, including its ability to identify diabetic retinopathy, branch retinal vein occlusion, central retinal vein occlusion, age-related macular degeneration, pathologic myopic choroidal neovascularization, and glaucoma-related optic nerve damage.\n\nThe results of this study are expected to support the development of standardized, efficient, and scalable AI-assisted diagnostic pathways for OCT imaging in clinical practice.",[58,28,113,114,115],"Age-Related Macular Degeneration (AMD)","Pathologic Myopia","Glaucoma","2025-11-18",{"date":118,"type":34},"2025-11-25",{"date":120,"type":21},"2025-11-30",{"date":122,"type":21},"2028-12-31",{"name":124,"class":41},"Peking Union Medical College Hospital",{"id":126,"slug":127,"hasResults":11,"nctId":128,"briefTitle":129,"officialTitle":130,"acronym":4,"eligibilityCriteria":131,"healthyVolunteers":50,"sex":16,"minAge":132,"maxAge":133,"enrollmentInfo":134,"targetDuration":4,"studyType":22,"phases":136,"briefSummary":138,"conditions":139,"keywords":142,"overallStatus":30,"whyStopped":4,"lastUpdateSubmitDate":145,"lastUpdatePostDateStruct":146,"startDateStruct":148,"completionDateStruct":150,"leadSponsor":152,"locationsCount":101},"100583667","early-phase-1-effectiveness-of-intravitreal-injection-of-aflibercept-8-mg-in-resistant-diabetic-macular-edema-retinal-vein-occlusion-and-myopic-choroidal-neovascularisation-patients-100583667","NCT06879301","Effectiveness of Intravitreal Injection of Aflibercept 8 mg in Resistant Diabetic Macular Edema, Retinal Vein Occlusion and Myopic Choroidal Neovascularisation Patients","Effectiveness of Intravitreal Injection of Aflibercept 8 mg in Resistant Diabetic Macular Edema and Retinal Vein Occlusion Patients","Inclusion Criteria:\n\nThis study included resistant centrally involved diabetic macular edema (DME) cases\n\n\\-\n\nExclusion Criteria:\n\n1. Patients with a history of intraocular surgery\n2. coincident retinal pathology such as retinal vascular occlusion, CNV due to age-related macular degeneration, angioid streaks, trauma, and choroiditis were excluded from the study.\n3. patients who received other lines of treatment for DME, such as laser photocoagulation, intravitreal injection of steroids\n4. patients known to be glaucomatous or have an IOP ≥20 mmHg were also excluded.\n\n   \\-","20 Years","60 Years",{"count":135,"type":21},60,[137],"EARLY_PHASE1","Generally, DM is caused by insufficient insulin secretion in the body; however, the other biological mechanisms remain unclear. Long-term illness in patients with DM damages various organs in the body, such as the eyes, kidneys, and heart, seriously affecting organ function. Nowadays, the quality of life of people has improved significantly, eating habits have changed, sugar intake is increasing, and the number of patients with DM is increasing. Statistics show that in 2017, the number of patients with DM worldwide reached 425 million (aged 20-79 years), which will exceed 600 million in 30 years; moreover, patients in low- and middle-income countries, such as China and India, account for 80 percent of the total DM population (1). According to the WHO, patients with DM worldwide increased to 366 million in 2011, which is expected to increase to 500 million in 2025, with more than 150 million patients experiencing ocular complications, such as diabetic retinopathy (DR) (2, 3). DR is a form of ocular microangiopathy and the most serious DM-related complication; it seriously endangers the health of patients with DM (4). DR pathogenesis includes increased endothelial cells in the eye capillaries, increased intimal thickness, damaged pericytes, microangioma, and damaged blood-retina barrier due to increased permeability of the blood vessels, microvascular obstruction, and neovascularization (NV) (5, 6). Currently, the prevalence of DR is 34.6% worldwide; however, it is higher in some developed countries, reaching 40.3% (7). The proportion of patients with type 1 and 2 DM suffering from blindness due to DR is 3.6% and 1.6%, respectively (8). DR is associated with significantly reduced living standards, huge medical costs, and increased social burden (9, 10).\n\nMany anti-vascular endothelial growth factor (VEGF) drugs exist; however, the use of therapeutic drugs is strictly controlled. The main drugs recommended for treating DM-related visual complications are ranibizumab and aflibercept.",[140,28,141],"Diabetic Macular Edema (DME)","Myopic Choroidal Neovascularisation",[143,144],"Aflibercept 8 mg","diabetic macular edema","2025-03-11",{"date":147,"type":34},"2025-03-17",{"date":149,"type":21},"2025-10-19",{"date":151,"type":21},"2025-12-19",{"name":153,"class":41},"Tanta University"]